Panel Data Stochastic Convergence Analysis of the Mexican Regions

The stochastic convergence amongst Mexican Federal entities is analyzed in panel data framework. The joint consideration of cross-section dependence and multiple structural breaks is required to ensure that the statistical inference is based on statistics with good statistical properties. Once these features are accounted for, evidence in favour of stochastic convergence is found. Since stochastic convergence is a necessary, yet insufficient condition for convergence as predicted by economic growth models, the paper also investigates whether-convergence process has taken place. We found that the Mexican states have followed either heterogeneous convergence patterns or divergence process throughout the analyzed period.

Asymptotic analysis of stock price densities and implied volatilities in mixed stochastic models

In this paper, we obtain sharp asymptotic formulas with error estimates for the Mellin con- volution of functions de ned on (0;1), and use these formulas to characterize the asymptotic behavior of marginal distribution densities of stock price processes in mixed stochastic models. Special examples of mixed models are jump-di usion models and stochastic volatility models with jumps. We apply our general results to the Heston model with double exponential jumps, and make a detailed analysis of the asymptotic behavior of the stock price density, the call option pricing function, and the implied volatility in this model. We also obtain similar results for the Heston model with jumps distributed according to the NIG law.

Numerical Dominance of the Argentine Ant vs Native Ants and Consequences on Soil Resource Searching in Mediterranean Cork-Oak Forests (Hymenoptera: Formicidae)

This study is focused on the dominance exerted by the invasive Argentine ant over native ants in a coastal Mediterranean area. Theimpact of this invasive ant on native ant assemblages and its consequences on total ant biomass and on the intensity of habitat explorationwere evaluated. Foraging ants were observed and their trajectories recorded during 5-minute periods in two study zones, one invaded andthe other non-invaded. Ant species detected, ant worker abundance, ant biomass and the intensity of soil surface searching done by antswere compared between the two zones. The Argentine ant invasion provoked a drastic reduction of the ant species richness. Apparentlyonly one native ant species is able to coexist with the Argentine ant, the cryptic Plagiolepis pygmaea. Ant worker abundance was also modified after the invasion: the number of Argentine ant workers detected, which represented 92% of the invaded zone, was two times higher than the number of native ant workers detected in the non-invaded zone. The total ant biomass was inversely affected, becoming four times lower in the invaded zone highly dominated by Linepithema humile. The higher number of Argentine ant workers and their fast tempo of activity implied an alteration of the intensity of soil surface searching: scanning by the Argentine ants in the invaded zone was higher than that done by the native ants in the non-invaded zone, and the estimated time for a complete soil surface scan was 64 minutes in the invaded zone and 108 minutes in the non-invaded zone. Consequently, resources will be discovered faster by ants in the invaded zone than in the non-invaded zone. The increase of the mean temperature and the decrease of the relative humidity from May to August reduced the ant activity in the two study zones but this reduction was greater in the invaded zone

PRACTICAL STOCHASTIC MODEL FOR CHEMICAL KINETICS

The Practical Stochastic Model is a simple and robust method to describe coupled chemical reactions. The connection between this stochastic method and a deterministic method was initially established to understand how the parameters and variables that describe the concentration in both methods were related. It was necessary to define two main concepts to make this connection: the filling of compartments or dilutions and the rate of reaction enhancement. The parameters, variables, and the time of the stochastic methods were scaled with the size of the compartment and were compared with a deterministic method. The deterministic approach was employed as an initial reference to achieve a consistent stochastic result. Finally, an independent robust stochastic method was obtained. This method could be compared with the Stochastic Simulation Algorithm developed by Gillespie, 1977. The Practical Stochastic Model produced absolute values that were essential to describe non-linear chemical reactions with a simple structure, and allowed for a correct description of the chemical kinetics.

Causation and dominance : a study of Finnish causative verbs expressing social dominance

En väsentlig fråga inom såväl lingvistiska som kognitiva teorier är, hur språket beskriver kausala relationer. I finskan finns det en speciell typ av kausativa verb avledda med suffixet (U)ttA som används för att uttrycka att handlingen i fråga utförs av någon annan än subjektreferenten, t.ex. Maija haetuttaa Matilla kirjastosta kirjan ’Maija låter Matti hämta boken från biblioteket’ och Matti juoksuttaa Maijan kaupunkiin ’Matti låter Maija springa till staden’. Syftet med denna avhandling var att med exempel av sociala dominansens kausativer undersöka ordbildningens natur samt begreppet ’socialt förorsakande’. För att beskriva avledningars regelbundna argumentstruktur i form av kopplingen mellan syntaxen och semantiken upprättades deras prototypiska strukturer. Dessa verb har emellertid också specifika användningsområden som framhäver variationer i sociala relationer. Säregna egenskaper hos den sociala dominansens kausativer inkluderades i undersökningen och definierades som konstruktioner. Konstruktionerna omfattar speciella syntaktiska och/eller semantiska element och utöver det också pragmatiska värderande implikationer. Uppbyggnaden av den sociala dimensionen hos de undersökta verben består av egenskaper förbundna med typen av förorsakande, argumentens agentiva egenskaper (aktivitet eller passivitet, dominans, kontroll, viljestyrdhet och ansvarighet) samt konventionaliserade attityder och tolkningar. Ett exempel på en s.k. 'tolkningskonstruktion’ är den negativa dominansens uttryck som i avhandlingen kallas Maktmissbrukskonstruktionen. Denna konstruktion inkluderar talarens starkt kritiska hållning till den uttryckta situationen, t.ex. Asiakas juoksuttaa lentoemäntää ’Kunden låter flygvärdinnan springa’. Dessa konstruktioner fyller en viktig funktion i språklig kommunikation: att beskriva avvikande av sociala normer och att foga expressivitet till budskapet. Metodologiskt kombinerar denna avhandling teorier som baseras på det aktuella språkbruket och teoretisk lingvistisk analys. Verbens samt konstruktionernas konceptuella lexikala struktur och prototypstrukturerna analyserades med hjälp av den konceptuella semantikens verktyg, som har utvecklats av Jackendoff, Nikanne och Pörn.

MCMC Analysis for Optimization of Stochastic Models

In any decision making under uncertainties, the goal is mostly to minimize the expected cost. The minimization of cost under uncertainties is usually done by optimization. For simple models, the optimization can easily be done using deterministic methods.However, many models practically contain some complex and varying parameters that can not easily be taken into account using usual deterministic methods of optimization. Thus, it is very important to look for other methods that can be used to get insight into such models. MCMC method is one of the practical methods that can be used for optimization of stochastic models under uncertainty. This method is based on simulation that provides a general methodology which can be applied in nonlinear and non-Gaussian state models. MCMC method is very important for practical applications because it is a uni ed estimation procedure which simultaneously estimates both parameters and state variables. MCMC computes the distribution of the state variables and parameters of the given data measurements. MCMC method is faster in terms of computing time when compared to other optimization methods. This thesis discusses the use of Markov chain Monte Carlo (MCMC) methods for optimization of Stochastic models under uncertainties .The thesis begins with a short discussion about Bayesian Inference, MCMC and Stochastic optimization methods. Then an example is given of how MCMC can be applied for maximizing production at a minimum cost in a chemical reaction process. It is observed that this method performs better in optimizing the given cost function with a very high certainty.

Stochastic variability of output levels in a pulp mill

Quite often, in the construction of a pulp mill involves establishing the size of tanks which will accommodate the material from the various processes in which case estimating the right tank size a priori would be vital. Hence, simulation of the whole production process would be worthwhile. Therefore, there is need to develop mathematical models that would mimic the behavior of the output from the various production units of the pulp mill to work as simulators. Markov chain models, Autoregressive moving average (ARMA) model, Mean reversion models with ensemble interaction together with Markov regime switching models are proposed for that purpose.

Stochastic approximation methods in stochastic optimization

Stochastic approximation methods for stochastic optimization are considered. Reviewed the main methods of stochastic approximation: stochastic quasi-gradient algorithm, Kiefer-Wolfowitz algorithm and adaptive rules for them, simultaneous perturbation stochastic approximation (SPSA) algorithm. Suggested the model and the solution of the retailer's profit optimization problem and considered an application of the SQG-algorithm for the optimization problems with objective functions given in the form of ordinary differential equation.

Numerical Simulation of Stochastic Di erential Equations

Stochastic differential equation (SDE) is a differential equation in which some of the terms and its solution are stochastic processes. SDEs play a central role in modeling physical systems like finance, Biology, Engineering, to mention some. In modeling process, the computation of the trajectories (sample paths) of solutions to SDEs is very important. However, the exact solution to a SDE is generally difficult to obtain due to non-differentiability character of realizations of the Brownian motion. There exist approximation methods of solutions of SDE. The solutions will be continuous stochastic processes that represent diffusive dynamics, a common modeling assumption for financial, Biology, physical, environmental systems. This Masters' thesis is an introduction and survey of numerical solution methods for stochastic differential equations. Standard numerical methods, local linearization methods and filtering methods are well described. We compute the root mean square errors for each method from which we propose a better numerical scheme. Stochastic differential equations can be formulated from a given ordinary differential equations. In this thesis, we describe two kind of formulations: parametric and non-parametric techniques. The formulation is based on epidemiological SEIR model. This methods have a tendency of increasing parameters in the constructed SDEs, hence, it requires more data. We compare the two techniques numerically.

Effect of the establishment of dominance relationships on cortisol and other metabolic parameters in Nile tilapia (Oreochromis niloticus)

The objective of the present study was to investigate the influence of the establishment of dominance relationships and social stress on plasma cortisol and metabolite levels in Nile tilapia (Oreochromis niloticus). During the 30-day experiment, the fish weighing 236 ± 29 g were kept in individual aquaria, except for two pairings lasting 6 h each. Blood samples were taken from the animals before and after pairing. Display, approach, attack, rebuff, chase flight, and coloration were carried out on days 16 and 30. Activities and behaviors characteristic of the establishment of dominance relationships were described. It was possible to classify all experimental fish (N = 30) as dominant or subordinate. No differences were detected between dominant (N = 15) and subordinate (N = 15) fish during isolation or after pairing in cortisol (isolated: 5.76 ± 0.98 vs 5.42 ± 0.63; paired: 10.94 ± 1.62 vs 11.21 ± 2.45 µg/dl), glucose (isolated: 60.02 ± 4.9 vs 67.85 ± 16.16; paired: 110.44 ± 15.72 vs 136.26 ± 22.46 mg/dl), triglyceride (isolated: 167.87 ± 5.06 vs 185.68 ± 7.24; paired: 210.85 ± 13.40 vs 221.82 ± 12.70 mg/dl) or total protein levels (isolated: 7.01 ± 0.42 vs 6.69 ± 0.59; paired: 9.21 ± 0.62 vs 9.51 ± 0.66 g/dl). However, when isolated (N = 30) and paired (N = 30) tilapia were compared, there were significant differences in cortisol and metabolite levels. The similar response presented by dominant and subordinate tilapia indicates that establishment of dominance relationships was a stressor for both groups.